Where is AI used in TruTalent?

Where is AI used in TruTalent?

TruTalent® uses artificial intelligence (AI) features to help organize, interpret, and explain candidate and job-related information. These tools are designed to support users in reviewing information more efficiently, but they do not make hiring or employment decisions.


AI is used to help process candidate information, such as importing resume details and converting them into structured data within MyData® Portfolio. This may include experience, education, certifications, skills, and related qualifications. It can also be used by candidates to create cover letters. AI also supports job content creation by helping generate job descriptions based on a job title and related market or occupational information, as well as by suggesting relevant skills and competencies associated with a role.


TruTalent is also used AI to classify and standardize information. For example, job descriptions may be mapped to occupational frameworks such as O*NET, and candidate or job information may be organized into categories such as roles, skills, and TruTalents®.


AI features also support candidate-job matching by generating match scores and evaluation summaries that explain how a candidate aligns with a specific role based on the information available within the platform. In addition, AI also interprets TruTalent assessment results by generating workplace strengths and employer-facing insights based on a candidate’s alignment with a role.


Automated systems, including AI-assisted review, are also used to help identify job postings or content that could violate platform policies, such as unlawful, discriminatory, misleading, or inappropriate content.


TruTalent also includes TalentScout, an interactive AI assistant that can answer questions about candidates, job descriptions, match results, and related platform information. For more information about TalentScout, visit our dedicated article: What is TalentScout?



Warning
AI-generated outputs should be reviewed and validated by users before being relied upon in decision-making.



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